Songbirds are a leading model of neurobiological research with wide implications for understanding issues of human health and disease. They are among the few organisms that have evolved vocal learning, a complex trait that provides the basis of spoken language acquisition in humans. Studies of the ontogeny of songbird vocalizations and the organization of the brain circuitry that controls song learning and production have provided unique opportunities for uncovering the neural bases of vocal learning. Songbird research has also contributed novel insights into a broad range of fundamental questions in neurobiology, such as behaviorally- regulated gene expression, sex dimorphisms and the effects of sex steroids on brain structure and function, photoperiodicity and the regulation of seasonal brain plasticity, the role of sleep in learning, the neuroendocrine regulation of reproductive and social behaviors, and neurogenesis and neuronal replacement in adulthood. To help understand how the song control circuitry and birdsong behavior are shaped by genetic mechanisms, a wide set of modern molecular and genomic resources have recently become available to songbird researchers through NIH-funded initiatives; such resources include normalized brain cDNA libraries, comprehensive annotated EST databases, microarrays, a BAC library and the completed the zebra finch genome. Such resources have been instrumental in the rapid identification of genes and gene families of neurobiological interest, the study of gene structure and regulatory domains, high- throughput analysis of gene regulation through molecular profiling studies, and comparative genomics across the major higher vertebrate groups. A key next step in making full use of these genomic resources and understanding how genes relate to brain function and behavior in songbirds is to map gene expression in the context of functional brain circuits. To achieve this goal, we propose a single Specific Aim, namely to generate a Gene Expression Brain Atlas of the Zebra Finch. Specifically we propose to map the brain expression of a large set of genes (~2,500) that are of key importance to songbird and avian brain researchers, in register with a histological atlas, and make the data available as a web-based resource.